import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'  # 去警告
import tensorflow as tf

def tensorboard_demo():
    """
    TensorBoard 可视化
    :return:
    """

    # a = tf.constant(2)
    # with tf.compat.v1.Session() as sess:
    #     tf.summary.create_file_writer('./resources/out')

    mnist = tf.keras.datasets.mnist

    (x_train, y_train), (x_test, y_test) = mnist.load_data()
    x_train, x_test = x_train / 255.0, x_test / 255.0

    model = create_model()
    model.compile(optimizer='adam',
                  loss='sparse_categorical_crossentropy',
                  metrics=['accuracy'])

    # log_dir为日志存放文件
    tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir="../resources/p02_deep_learning_tensorFlow/tensorboard_out", histogram_freq=1)

    model.fit(x=x_train,
              y=y_train,
              epochs=5,
              validation_data=(x_test, y_test),
              callbacks=[tensorboard_callback])

    return None

def create_model():
    return tf.keras.models.Sequential([
        tf.keras.layers.Flatten(input_shape=(28, 28)),
        tf.keras.layers.Dense(512, activation='relu'),
        tf.keras.layers.Dropout(0.2),
        tf.keras.layers.Dense(10, activation='softmax')
    ])

if __name__ == "__main__":
    # 代码4：TensorBoard 可视化
    tensorboard_demo()